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  • Research Article
  • Open Access

Downlink Multicell Processing with Limited-Backhaul Capacity

EURASIP Journal on Advances in Signal Processing20092009:840814

  • Received: 16 November 2008
  • Accepted: 18 May 2009
  • Published:


Multicell processing in the form of joint encoding for the downlink of a cellular system is studied under the assumption that the base stations (BSs) are connected to a central processor (CP) via finitecapacity links (finite-capacity backhaul). To obtain analytical insight into the impact of finite-capacity backhaul on the downlink throughput, the investigation focuses on a simple linear cellular system (as for a highway or a long avenue) based on theWyner model. Several transmission schemes are proposed that require varying degrees of knowledge regarding the system codebooks at the BSs. Achievable rates are derived in closed-form and compared with an upper bound. Performance is also evaluated in asymptotic regimes of interest (high backhaul capacity and extreme signal-to-noise ratio, SNR) and further corroborated by numerical results. The major finding of this work is that even in the presence of oblivious BSs (that is, BSs with no information about the codebooks) multicell processing is able to provide ideal performance with relatively small backhaul capacities, unless the application of interest requires high data rate (i.e., high SNR) and the backhaul capacity is not allowed to increase with the SNR. In these latter cases, some form of codebook information at the BSs becomes necessary.


  • Quantum Information
  • Ideal Performance
  • High Data
  • Cellular System
  • Central Processor

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Authors’ Affiliations

CWCSPR, New Jersey Institute of Technology, Newark, NJ 07102, USA
Department of Electrical Engineering, Princeton University, Princeton, NJ 08544, USA
Department of Electrical Engineering, Technion, Haifa, 32000, Israel


© O. Simeone et al. 2009

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.